Particle Filtering for Quantized Sensor Information
2005 (English)In: Proceedings of the 13th European Signal Processing Conference, 2005, 201-204 p.Conference paper (Refereed)
The implication of quantized sensor information on filtering problems is studied. The Cramer-Rao lower bound (CRLB) is derived for estimation and filtering on quantized data. A particle filter (PF) algorithm that approximates the optimal nonlinear filter is provided, and numerical experiments show that the PF attains the CRLB, while second-order optimal Kalman filter (KF) approaches can perform quite bad.
Place, publisher, year, edition, pages
2005. 201-204 p.
Cramér-Rao lower bound, Particle filter, Kalman filter
National CategoryEngineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-29613Local ID: 14992ISBN: 9781604238211OAI: oai:DiVA.org:liu-29613DiVA: diva2:250430
13th European Signal Processing Conference, Antalya, Turkey, September, 2005